International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
1
Working Capital Management and Firm Profitability: Empirical Evidence
from Manufacturing and Construction Firms Listed on Nairobi Securities
Exchange, Kenya
Daniel Mogaka Makori1
Ambrose Jagongo, PhD2
Abstract
Working capital management plays a significant role in improved profitability of firms.
Firms can achieve optimal management of working capital by making the trade-off
between profitability and liquidity. This paper analyzes the effect of working capital
management on firm’s profitability in Kenya for the period 2003 to 2012. For this
purpose, balanced panel data of five manufacturing and construction firms each which
are listed on the Nairobi Securities Exchange (NSE) is used. Pearson’s correlation and
Ordinary Least Squares regression models were used to establish the relationship
between working capital management and firm’s profitability. The study finds a
negative relationship between profitability and number of day’s accounts receivable
and cash conversion cycle, but a positive relationship between profitability and number
of days of inventory and number of day’s payable. Moreover, the financial leverage,
sales growth, current ratio and firm size also have significant effects on the firm’s
profitability. Based on the key findings from this study it has been concluded that the
management of a firm can create value for their shareholders by reducing the number
of day’s accounts receivable. The management can also create value for their
shareholders by increasing their inventories to a reasonable level. Firms can also take
long to pay their creditors in as far as they do not strain their relationships with these
creditors. Firms are capable of gaining sustainable competitive advantage by means of
effective and efficient utilization of the resources of the organization through a careful
reduction of the cash conversion cycle to its minimum. In so doing, the profitability of
the firms is expected to increase.
Keywords: Working Capital Management, Average Collection Period, Average
Inventory Period, Average Payment Period, Cash Conversion Cycle, Return on Assets,
manufacturing and construction firms
1. Introduction
The concept of working capital management addresses companies’ managing of their short-term
capital and the goal of the management of working capital is to promote a satisfying liquidity,
profitability and shareholders’ value. Working capital management is the ability to control effectively
and efficiently the current assets and current liabilities in a manner that provides the firm with maximum
return on its assets and minimizes payments for its liabilities.
1
2
Lecturer, Department of Accounting and Finance, School of Business, Kenyatta University, Kenya
Lecturer, Department of Accounting and Finance, School of Business, Kenyatta University, Kenya
©American Research Institute for Policy Development
www.aripd.org/ijat
2
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
The short-term capital refers to the capital that companies use in their daily operations and it
consists of companies’ current assets and current liabilities. A well managed working capital promotes a
company’s well being on the market in terms of liquidity and it also acts in favor for the growth of
shareholders value (Jeng-Ren, Li & Han-Wen, 2006).
Working capital management efficiency is vital especially for manufacturing and construction
firms, where a major part of assets is composed of current assets (Horne & Wachowitz, 2000). It
directly affects the profitability and liquidity of firms (Raheman & Nasr, 2007). The profitability
liquidity tradeoff is important because if working capital management is not given due considerations
then the firms are likely to fail and face bankruptcy (Kargar & Bluementhal, 1994). The significance of
working capital management efficiency is irrefutable (Filbeck & Krueger, 2005). Working capital is
known as life giving force for any economic unit and its management is considered among the most
important function of corporate management. Every organization whether, profit oriented or not,
irrespective of size and nature of business, requires necessary amount of working capital. Working
capital is the most crucial factor for maintaining liquidity, survival, solvency and profitability of
business (Mukhopadhyay, 2004). Working capital management is one of the most important areas while
making the liquidity and profitability comparisons among firms (Eljelly, 2004), involving the decision
of the amount and composition of current assets and the financing of these assets. The greater the
relative proportion of liquid assets, the lesser the risk of running out of cash, all other things being
equal. All individual components of working capital including cash, marketable securities, account
receivables and inventory management play a vital role in the performance of any firm.
Efficient management of working capital plays an important role of overall corporate strategy in
order to create shareholder value. Working capital is regarded as the result of the time lag between the
expenditure for the purchase of raw material and the collection for the sale of the finished goods. The
way of managing working capital can have a significant impact on both the liquidity and profitability of
the company (Shin & Soenen, 1998). The main purpose of any firm is to maximize profit. But,
maintaining liquidity of the firm also is an important objective. The problem is that increasing profits at
the cost of liquidity can bring serious problems to the firm. Thus, strategy of firm must maintain a
balance between these two objectives of the firms. Dilemma in working capital management is to
achieve desired tradeoff between liquidity and profitability (Smith, 1980; Raheman & Nasr, 2007).
Referring to theory of risk and return, investment with more risk will result to more return. Thus, firms
with high liquidity of working capital may have low risk and low profitability. Conversely, a firm that
has low liquidity of working capital faces high risk which results to high profitability.
In Kenya, the industrial sector is the fourth biggest sector after agriculture, transport and
communication and wholesale and retail trade. The sector had 17 firms listed at Nairobi Securities
Exchange (NSE) in 2010 but was split into four sectors in 2011 namely, the automobile and accessories,
construction, energy and petroleum, and manufacturing sectors. It contributed about 10.1 per cent of
Kenya’s GDP serving both the local market and exports to the East African region. The sector, which is
dominated by subsidiaries of multi-national corporations, contributed approximately 18% of the Gross
Domestic Product (GDP) in 2009 (NSE Handbook, 2010, 2011). As an important sector in the overall
economic growth, manufacturing sector requires in depth analysis at industry as well as firm level. As at
the end of 2012, there were eighteen (18) manufacturing and construction firms listed in the NSE
Exchange with the price movement of 5 of them being used to determine the daily average NSE index.
Considering the importance of working capital management the researchers focused on analyzing
relationship between working capital management and profitability relationship such as Gul, Khan,
Rehman, Khan, Khan and Khan (2013); Oladipupo and Okafor (2013); Almazari, (2013); Akoto,
Awunyo-Vitor and Angmor (2013); Maradi, Salehi and Arianpoor (2012); Nyabwanga, Ojera,
Lumumba, Odondo and Otieno (2012); Sharma and Kumar (2011); Raheman, Afza, Qayyum and Bodla
(2010); and Gill, Biger and Mathur (2010) among others.
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
3
However, there are a few studies with reference to Kenya on working capital management and
firm profitability, especially in the manufacturing and construction sectors. For example, Mathuva
(2010) focused on the influence of working capital management on corporate profitability of firms listed
at the Nairobi Securities Exchange. Gakure, Cheluget, Onyango and Keraro (2012) on the other hand,
analyzed the relationship between working capital management and performance of 15 manufacturing
firms listed at the Nairobi Securities Exchange for a period of five years from 2006 to 2010. Omesa,
Maniagi, Musiega and Makori (2013) examined the relationships between Working Capital
Management and Corporate Performance of 20 manufacturing firms listed on the Nairobi securities
exchange for 5 years from 2007-2011 was selected. Finally, Nyabwanga, Ojera, Lumumba, Odondo, &
Otieno (2012) assessed the effect of working capital management practices on the financial performance
of SSEs in Kisii South District. However, these studies provide no evidence on the relationship between
working capital management and profitability of manufacturing and construction firms in Kenya. In this
context, the objective of the current study is to provide empirical evidences about the effect of working
capital management on profitability for a sample of 10 manufacturing and construction companies
during the period 2003–2013.
The paper is structured as follows: the second section deals with brief review of important
theoretical and empirical literature on the relationship between working capital management and firm
profitability; the third section provides the conceptual framework while the fourth section indicates the
objectives of the study and the research hypotheses. The fifth and sixth sections present methodology
employed; and the data analysis and findings of the study respectively. Finally, the main conclusions
and recommendations are discussed in seventh and eighth sections respectively.
2. Review of Literature
Various studies have analyzed the relationship of working capital management (WCM) and firm
profitability in various markets. The results are quite mixed, but a majority of studies conclude a
negative relationship between WCM and firm profitability. The studies reviewed have used various
variables to analyze the relationship, with different methodology such as linear regression and panel
data regression. This section presents the chronology of major studies related to this study in order to
assess and identify the research gap.
Gul, Khan, Rehman, Khan, Khan and Khan (2013) investigated the influence of working capital
management (WCM) on performance of small medium enterprises (SMEs) in Pakistan. The duration of
the study was seven years from 2006 to 2012. The data used in this study was taken from SMEDA,
Karachi Stock Exchange, tax offices, company itself and Bloom burgee business week. The dependent
variable of the study was Return on Assets (ROA) which was used as a proxy for profitability.
Independent variables were Number of Days Account Receivable (ACP), Number of Day’s Inventory
(INV), Cash Conversion Cycle (CCC) and Number of Days Account Payable (APP). In addition to
these variables some other variables were used which included Firm Size (SIZE), Debit Ratio (DR) and
Growth (GROWTH). Regression analysis was used to determine the relationship between WCM and
performance of SMEs in Pakistan. Results suggested that APP, GROWTH and SIZE have positive
association with Profitability whereas ACP, INV, CCC and DR have inverse relation with profitability.
Oladipupo and Okafor (2013) examined the implications of a firm’s working capital
management practice on its profitability and dividend payout ratio. The study focused on the extent of
the effects of working capital management on the Profitability and Dividend Payout Ratio. Financial
data were obtained from 12 manufacturing companies quoted on the Nigeria Stock Exchange over 5
years period (2002 to 2006). Using both the Pearson product moment correlation technique and ordinary
least square (OLS) regression technique, they observed that shorter net trade cycle and debt ratio
promote high corporate profitability. While the level of leverage has negative significant impact on
corporate profitability, the impacts of working capital management on corporate profitability appeared
to be statistically insignificant at 5% confidence level.
©American Research Institute for Policy Development
www.aripd.org/ijat
4
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
On the other hand, they observed that dividend payout ratio was influenced positively by
profitability and net trade cycle but negatively by growth rate in earnings.
Almazari (2013) investigated the relationship between the working capital management (WCM)
and the firms’ profitability for the Saudi cement manufacturing companies. The sample included 8
Saudi cement manufacturing companies listed in the Saudi Stock Exchange for the period of 5 years
from 2008-2012. Pearson Bivariate correlation and regression analysis were used. The study results
showed that Saudi cement industry’s current ratio was the most important liquidity measure which
effected profitability, therefore, the cement firms must set a trade-off between these two objectives so
that, neither the liquidity nor profitability suffers. It was also found, as the size of a firm increases,
profitability increased. Besides, when the debt financing increased, profitability declined. Linear
regression tests confirmed a high degree of association between the working capital management and
profitability.
Akoto, Awunyo-Vitor and Angmor (2013) analyzed the relationship between working capital
management practices and profitability of listed manufacturing firms in Ghana. The study used data
collected from annual reports of all the 13 listed manufacturing firms in Ghana covering the period from
2005-2009. Using panel data methodology and regression analysis, the study found a significant
negative relationship between Profitability and Accounts Receivable Days. However, the firms’ Cash
Conversion Cycle, Current Asset Ratio, Size, and Current Asset Turnover significantly positively
influence profitability. The study suggests that managers can create value for their shareholders by
creating incentives to reduce their accounts receivable to 30 days. It is further recommended that,
enactments of local laws that protect indigenous firms and restrict the activities of importers are eminent
to promote increase demand for locally manufactured goods both in the short and long runs in Ghana.
Omesa, Maniagi, Musiega and Makori (2013) examined the relationships between Working
Capital Management and Corporate Performance of manufacturing firms listed on the Nairobi securities
exchange. A sample of 20 companies whose data for 5 years from 2007-2011 was selected. For analysis
Principal components analysis (PCA) is used due to its simplicity and its capacity of extracting relevant
information from confusing data sets. From the results using PAC and multiple regression, working
capital proxies Cash Conversion Cycle (CCC), Average Collection Period (ACP) and control variables
Current Liabilities (CLTA), Net Working Capital Turnover Ratio (NSCA) and Fixed Financial Ratio
(FATA) were significant at 95% confidence (p values are < 0.05) to performance as measured by Return
on Equity (ROE). Further, ACP was found to be negatively related to ROE while CCC, CLATA, NSCA
and FATA.
Maradi, Salehi and Arianpoor (2012) compared working capital management of two groups of
listed companies in Tehran Stock Exchange (TSE), which comprised of chemical industry and medicine
industry. In chemical industry, 34 companies and medicine industry, 30 companies were selected and
information related to these companies was gathered over 10 years (2001-2010) and analyzed using
OLS multiple regression. The results show that, in medicine industry compared to chemical industry,
debt ratio makes more impact on reduction of net liquidity. But examination of impact of LEV over
WCR indicate that, in chemical industry, debt ratio makes more impact on reduction of working capital
requirements, compared to medicine industry.
Nyabwanga, Ojera, Lumumba, Odondo and Otieno (2012) assessed the effect of working capital
management practices on the financial performance of SSEs in Kisii South District. A sample of 113
SSEs comprising 72 trading and 41 manufacturing enterprises was used. Pearson’s correlation
coefficients and multiple regression analysis techniques were used to analyze data. Consequently, the
findings of the study were that, working capital management practices were low amongst SSEs as
majority had not adopted formal working capital management routines and their financial performance
was on a low average.
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
5
The study also revealed that SSE financial performance was positively related to efficiency of
cash management (ECM), efficiency of receivables management (ERM) and efficiency of inventory
management (EIM).
Gakure, Cheluget, Onyango and Keraro (2012) analyzed the relationship between working
capital management and performance of 15 manufacturing firms listed at the Nairobi NSE from 2006 to
2010 and for a total 75 firms year observations. They used secondary data from a sample of 18
companies at the NSE. A regression model was used to establish the relationship between the dependent
variable and the independent variables. Pearson’s correlation and regression analysis were used for the
analysis. The results indicated that there is a strong negative relationship between firm’s performance
and liquidity of the firm. The study found that there is a negative coefficient relationship between
accounts collection period, average payment period, inventory holding period and profitability while the
cash conversion cycle was found to be positively correlated with profitability. However, the effects of
the independent variables except the average payment period were no statistically significant though the
overall model was statistically significant.
Sharma and Kumar (2011) examined the effect of working capital on profitability of Indian
firms. They collected data about a sample of 263 non-financial BSE 500 firms listed at the Bombay
Stock (BSE) from 2000 to 2008 and evaluated the data using OLS multiple regression. The results
revealed that working capital management and profitability is positively correlated in Indian companies.
The study further reveals that inventory of number of days and numbers of day’s accounts payable are
negatively correlated with a firm’s profitability, whereas number of days accounts receivables and cash
conversion period exhibit a positive relationship with corporate profitability.
Raheman, Afza, Qayyum and Bodla (2010) analyzed the impact of working capital management
on firm’s performance in Pakistan for the period 1998 to 2007. For this purpose, balanced panel data of
204 manufacturing firms was used which are listed on Karachi Stock Exchange. The results indicate that
the cash conversion cycle, net trade cycle and inventory turnover in days are significantly affecting the
performance of the firms. They concluded that manufacturing firms were in general facing problems
with their collection and payment policies. Moreover, financial leverage, sales growth and firm size also
had significant effect on the firm’s profitability. They study recommended that effective policies must
be formulated for the individual components of working capital.
Mathuva (2010) in his study on the influence of working capital management on corporate
profitability found that there exists a highly significant negative relationship between the time it takes
for firms to collect cash from their customers and profitability. He explained that the more profitable
firms take the shortest time to collect cash from the customers. The study further revealed that there
exist a highly significant positive relationship between the inventory conversion period and profitability.
It was explained that firms, which maintain sufficiently high inventory levels reduce costs of possible
interruptions in the production process and loss of business due to scarcity and products. Finally, the
study established that there exists a highly significant positive significant positive relationship between
the average payment period and profitability. He held that the longer a firm takes to pay its creditors, the
more profitable it is. In this study, a sample of 30 firms listed on Nairobi Stock Exchange for the periods
1993 to 2008 was used. Both the ported OLS and the fixed effects regression models were used.
Gill, Biger and Mathur (2010) analyzed the relationship between working capital management
and profitability of 88 American firms listed on New York Stock Exchange for a period of 3 years from
2005 to 2007 was selected. The data was analyzed using Pearson Bivariate Correlation Analysis and
Weighted Least Squares (WLS) Regression techniques. They found statistically significant relationship
between the cash conversion cycle and profitability, measured through gross operating profit. It
followed that managers can create profits for their companies by handling correctly the cash conversion
cycle and by keeping accounts receivables at an optimal level.
©American Research Institute for Policy Development
www.aripd.org/ijat
6
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
Although studies on working capital management have been carried out by various scholars such
as Gul, Khan, Rehman, Khan, Khan and Khan (2013); Oladipupo and Okafor (2013); Ahmad (2013);
Akoto, Awunyo-Vitor and Angmor (2013); Omesa, Maniagi, Musiega and Makori (2013); Maradi,
Salehi and Arianpoor (2012); Gakure, Cheluget, Onyango and Keraro (2012); Sharma and Kumar
(2011); Mathuva (2010); and Gill, Biger and Mathur (2010, it is instructive to note that there is still
ambiguity regarding the appropriate variables that might serve as proxies for working capital
management. These studies do not provide clear-cut direction of the relationship between working
capital and firm’s profitability. Further examination of these studies reveals that there is little of
empirical evidence on the working capital management and its impact on the firm profitability in case of
manufacturing and construction sectors of Kenya. Therefore, the present study is an attempt to fill this
gap and estimates the relationship between working capital management variables (Average Collection
Period, Inventory Conversion Period, Average Payment Period and Cash Conversion Cycle) and firm
profitability of manufacturing and construction firms in Kenya.
3. Conceptual Framework
Figure 1 below presents schematic conceptual framework of the relationship between working
capital management measures and profitability of firms.
Independent Variables
 Average Collection Period

Inventory Conversion Period

Average Payment Period

Cash Conversion Cycle
Dependent Variable
 Profitability of the Firm
Control Variables
 Sales Growth

Firm Leverage

Current Ratio

Firm Size
Figure 1: Schematic Conceptual Framework
Source: Author (2013)
4. Objectives of the Study and Research Hypotheses
4.1 General Objective
The main objective of the paper is to examine the relationship between working capital
management and profitability of manufacturing and construction firms listed on the Nairobi Securities
Exchange (NSE).
4.2 Specific Objectives
To achieve the general objective, the following specific objectives were used:
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
i.
ii.
iii.
iv.
7
To determine whether there is a significant relationship between Average Collection Period
(ACP) and Profitability of the firm.
To establish whether there is a significant relationship between Inventory Conversion Period
(ICP) and Profitability of the firm.
To ascertain if there is a significant relationship between Average Payment Period (APP) and
Profitability of the firm.
To examine if there is a significant relationship between Cash Conversion Cycle (CCC) and
Profitability of the firm.
4.3 Research Hypotheses
i.
ii.
iii.
iv.
Ho1: There is no significant relationship between Average Collection Period (ACP)
Profitability of the firm.
Ho2: There is no significant relationship between Inventory Conversion Period (ICP)
Profitability of the firm.
Ho3: There is no significant relationship between Average Payment Period (APP)
Profitability of the firm.
Ho4: There is no significant relationship between Cash Conversion Cycle (CCC)
Profitability of the firm.
and
and
and
and
5. Research Methodology
5.1
Model Specification
Consistent with previous studies (Nazir & Afza, 2009); Zariyawati, et al., 2008; Samiloglu &
Demirgunes, 2008; and Garcia-Teruel & Martinez-Solano, 2007) the firm’s profitability is modeled as a
function of the four core working capital management measures in addition to other firm characteristics.
The effects of working capital management on the firm's profitability are modeled using the following
OLS regression equations to obtain the estimates:
ROA = f (ACP, ICP, APP, CCC, GROWTH, LEV, CR, SIZE)
Model 1: ROA = β + β GROWTH + β DR + β CR + β SIZE + β ACP + ε
Model 2: ROA = β + β GROWTH + β DR + β CR + β SIZE + β ICP + ε
Model 3: ROA = β + β GROWTH + β DR + β CR + β SIZE + β APP + ε
Model 4: ROA = β + β GROWTH + β DR + β CR + β SIZE + β CCC + ε
Model5:ROA = β + β ACP + β ICP + β APP + β GROWTH + β DR + β CR +
β SIZE + ε
Where, ROA denotes the return on assets, GROWTH is the sales growth, DR is the debt ratio,
SIZE is the company size as measured by natural logarithm of total assets, CR is the current ratio, ACP
is the average collection period, ICP is the inventory conversion period, APP is the average payment
period and CCC is the cash conversion cycle. Subscripts i denote firms (cross-section dimensions)
ranging from 1 to 10, t denotes years (time-series dimensions) ranging from 1 to 10, ε is the error term
of the model and β0, β1, β2, β3, β4, β5=Regression model coefficients. In the first regression model, the
ACP has been regressed against the ROA. In the second regression model, the ICP has been regressed
against the ROA. The third regression model involves a regression of the APP against the ROA. In the
fourth regression model, the CCC is regressed against the ROA. Finally, the three working capital
measures (ACP, ICP and AP) have been regressed together against the ROA. The CCC was not
included in the last regression model because its inclusion results to a high degree of multicollinearity
among the working capital management variables as shown by the variance inflation factors (VIFs)
(Montgomery et al., 2007).
©American Research Institute for Policy Development
www.aripd.org/ijat
8
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
5.2 Data and Variables
Data for this study was collected from the listed firms on the NSE for the period 2003-2012.
Consistent with Barako et al. (2006), data were obtained from the NSE handbooks and the Kenya
Capital Markets Authority. The required financial data of these firms was obtained from the companies’
annual reports. Consequently, the sample data begins in 2003 and ends in 2012 in order to ensure
accuracy of the collected data and a number of filters were applied. Observations of items from the
balance sheet and profit and loss accounts showing signs contrary to reasonable expectations were
removed. Thus a balanced panel dataset of 100 firm year observation was obtained, with observation of
10 firms between 2003 and 2013.
In order to analyze the effects of working capital components on the profitability of
manufacturing and construction companies in Kenya, profitability is measured by Return on Assets
(ROA), which is defined as the ratio of earnings before interest and tax to total assets. ROA is used as a
dependent variable. ROA has been used by Samiloglu and Demirgunes (2008), Garcia-Teruel and
Martinez-Solano (2007) and Nazir and Afza (2009). The return on assets determines the management
efficiency to use assets generates earnings. It is a better measure since it relates the profitability of the
company to the asset base (Padachi, 2006).
The average collection period (ACP); the inventory conversion period (ICP); the average
payment period (APP); and the Cash Conversion Cycle are used as the independent variables and are
considered for measuring working capital management. ACP is the time taken to collect cash from
customers; ICP refers to the time taken to convert inventory held in the firm into sales; APP is the time
taken to pay the firm’s suppliers while CCC is used as a comprehensive measure of working capital as it
shows the time-lag between payment for the purchase of raw material and the collection of sales of
finished goods. Apart from these variables, the size of the firm, the growth in its sales, firm leverage and
current ratio are introduced as control variables. The reason for choosing these variables is that most of
researchers (Deloof, 2003; Garcia-Teruel & Martinez-Solano, 2007; Jose et al., 1996; Nazir & Afza,
2009; Raheman & Nasr, 2007; Huang et al. (2009); and Shin & Soenen, 1998) have used these to
calculate the relationship between WCM and profitability in various markets. Table 1 below presents
the variables, abbreviations and their measurements as used in the analysis.
Table 1: Abbreviation and Measurement of Variables
Variable
Return on Assets
Average Collection Period
Inventory Conversion Period
Average Payment Period
Cash Convention Cycle
Sales Growth
Debt Ratio
Current Ratio
Firm Size
Abbreviation
ROA
ACP
ICP
APP
CCC
GROWTH
DR
CR
SIZE
Measurement
Earnings Before Tax And Interest/Total Assets
Accounts Receivable/Net Sales*365
Inventory/Cost of Sales*365
Accounts Payable/Cost of Sales*365
ACP + ICP – APP
(Salest – Salest-1)/Salest-1
Total Liabilities/Total Assets
Current assets/Current Liabilities
Ln(Total Assets)
Source: Author (2013)
6. Empirical Analysis
In this section, the empirical results are presented from quantitative data analysis using and EViews and SPSS. Descriptive analysis is presented first followed by the Pearson’s correlation and
regression analysis.
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
9
6.1 Descriptive Statistics
Descriptive analysis shows the mean, and standard deviation of the different variables of
interest in this study. It also presents the minimum and maximum values of the variables which help in
getting a picture about the maximum and minimum values a variable has achieved.
Table 2: Descriptive Statistics of Variables for Manufacturing Firms
Variable
ROA
ACP
ICP
APP
CCC
GROWTH
LEV
CR
SIZE
Mean
0.157
56.535
93.851
96.503
53.883
0.161
0.439
2.513
15.668
Median
0.135
52.812
85.949
86.099
48.612
0.149
0.426
1.719
15.826
SD
0.104
32.476
47.652
49.846
54.538
0.185
0.165
2.628
1.180
Minimum
-0.052
8.747
27.135
18.969
-89.363
-0.313
0.144
0.803
12.782
Maximum
0.379
174.390
249.527
264.555
201.210
0.926
0.881
14.681
17.815
Source: 2003-2012 Survey Data, E-Views & SPSS Output
Table 2 presents the summary statistics of the variables used in the present study for 100 firm year
observations were used. The mean value of return on assets is 15.7% with a standard deviation of
10.8%. The mean accounts collection period is 56.535 days with a standard deviation of 32.476 days.
On average, firms take 93.851 days (approximately three months) to convert their inventories into sales
with a standard deviation of 47.652 days. The table also shows that on average the firms take 96.503
days to pay its creditors with a standard deviation of 49.846 days. The mean cash conversion cycle is
53.883 days. The table further shows that an average firm has a size of 15.668 as measured by the
natural logarithm of its total assets. The mean leverage ratio is 43.9% lagged by total assets. The typical
firm in the sample has a current assets ratio of 2.513. Together with this, the firms have seen their sales
growth by almost 16.1% annually on an average.
6.2 Pearson Correlations Analysis
Consistent with Sharma and Kumar (2011), Table 3 shows both the Pearson correlations among the
observed variables.
Table 3: Pearson Bivariate Correlation Coefficients
ROA
ACP
ICP
APP
CCC
GROWTH
LEV
CR
SIZE
ROA
1
-0.161
0.265**
0.552**
-0.370**
0.133
-0.419**
0.181
0.243*
ACP
ICP
APP
CCC
Growth
LEV
CR
Size
1
-0.026
0.026
0.549**
0.127
0.068
0.187
-0.418**
1
0.562**
0.344**
0.052
0.151
-0.249*
-0.000
1
-0.407**
-0.127
-0.036
-0.078
0.354**
1
0.237*
0.205*
-0.034
-0.574**
1
0.119
0.013
-0.249*
1
-0.572**
0.134
1
-0.409**
1
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed).
Source: 2003-2012 Survey Data, E-Views & SPSS Output
©American Research Institute for Policy Development
www.aripd.org/ijat
10
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
Table 3 shows that the ROA is negatively related to ACP, CCC and LEV. The negative relation
between ROA and ACP is consistent with the view that the less the time taken by customers to pay their
bills, the more cash is available to replenish the inventory hence leading to more sales which result to an
increase in profitability. The negative relationship between ROA and CCC is consistent with the view
that the time lag between the expenditure for the purchases of raw materials and the collection of sales
of finished goods can be too long and that decreasing this time lag increases profitability (Deloof, 2003).
The Table also shows that the ROA is positively related to ICP, APP, GROWTH, CR and SIZE. The
positive relationship between ROA and ICP can be explained by the fact that firms which maintain high
inventory levels reduce the cost of possible interruptions in the production process. This helps in
preventing loss of business due to the scarcity of products and reducing the cost of supplying the goods.
In so doing, firms are protected against price fluctuations (Blinder & Maccrni, 1991).
The positive relation between ROA and APP can be explained by the fact that lagging payments
to suppliers ensures that the firm has some cash to purchase more inventory for sale thus increasing its
sales levels hence boosting its profits. Further, Firm size is positively related to ROA which means that
larger firms report higher profits compared to smaller firms. This may be due to larger firm's ability to
exploit the economies of scale. The correlation coefficients of Inventory Conversion Period, Average
Payment Period, Cash Conversion Cycle, Firm Leverage and Company Size are significant while the
correlation coefficients of Average Collection Period, the Sales Growth and Current Ratio are not
significant.
6.3 Regression
In order to test the hypotheses, pooled OLS regression analysis has been conducted to determine
the whether there is significant relationship between working capital management and profitability.
Results in Table 4 and 5 provide results for the models tested in the present study. In order to check the
presence of autocorrelation and multicollinearity in the data, Durbin Watson (D-W) and Variance
Inflation Factor (VIF) statistics was analyzed respectively.
Table 4: Variance Inflation Factor
Parameter
ACP
ICP
APP
CCC
GROWTH
LEV
CR
SIZE
Model 1
1.254
Model 2
Model 3
Model 4
1.081
1.155
1.094
1.588
1.811
1.491
1.095
1.537
1.883
1.320
1.095
1.541
1.786
1.465
1.781
1.099
1.586
1.865
2.105
Model 5
1.387
1.978
2.218
1.100
1.612
1.992
2.154
Source: 2003-2012 Survey Data, SPSS Output
It is evident that the statistics are within the limit, leading to the conclusion that there is no
presence of autocorrelation and multicollinearity in the data. The highest value of VIF statistics obtained
is 2.218 whereas a commonly given rule of thumb is that VIF’s of 10 or higher may be a reason for
concern (Gujarati & Sangeetha, 2008). D-W statistics value was found to be 1.137 in model 2, which
was highest in all five models. Durbin-Watson statistic ranges in value from 0 to 4 with an ideal value of
2 indicating that errors are not correlated, although values from 1.75 to 2.25 may be considered
acceptable. Further some authors (Makridakis & Wheelwright, 1978) consider D-W value between 1.5
and 2.5 as acceptable level indicating no presence of collinearity.
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
11
Table 5: OLS Regression Results
Dependent Variable: Return on Assets (ROA)
Parameter
Model 1
Model 2
Constant
-0.306 (0.053)*
-0.459
(0.001)***
ACP
-3.98E-005
(0.894)
ICP
0.001
(0.000)***
APP
CCC
GROWTH
LEV
0.163
(0.001)***
-0.289 (0.00)***
CR
SIZE
0.003 (0.468)
0.036***
Adjusted R2
F-Value
0.312
9.989
(0.000)***
0.847
100
D-W Statistic
Firm Years
0.157
(0.001)***
-0.288
(0.000)***
0.008 (0.067)*
0.040
(0.000)***
0.444
16.780
(0.000)***
1.137
100
Model 3
-0.166 (0.170)
Model 4
-0.128 (0.476)
Model 5
-0.115 (0.440)
-0.0003
(0..130)
0.0001 (0.546)
0.001
(0.000)***
0.170
(0.001)***
-0.271
(0.000)***
0.002 (0.511)
0.020
(0.000)***
0.540
24.273
(0.000)***
1.217
100
0.001
(0.000)***
-0.000 (0.091)*
0.168
(0.001)***
-0.271
(0.000)***
0.002 (0.722)
0.025
(0.019)**
0.333
10.874
(0.000)***
0.836
100
0.170
(0.000)***
-0.256
(0.000)***
0.004 (0.319)
0.017 (0.060)*
0.547
18.045***
1.282
100
*, **and ***Denotes significance level at 10%, 5% & 1% levels, respectively
Source: 2003-2012 Survey Data, E-Views & SPSS Output
Model 1 tests the hypothesis that there is no significant relationship between Average
Collection Period and profitability. The regression results indicates that the coefficient of ACP is
negative with -3.98E-005, but it is not significantly different from zero (p-value =0.894). Thus, Ho1
hypothesis is not rejected and is concluded that ACP is not statistically significant at 1% significance
level (p>0.01). This suggests that, though short ACP is good for explaining the financial success of
listed manufacturing and construction firms in Kenya, it is not a critical factor to consider when taking
decision to improve profitability. The result is consistent with Raheman, Afza, Qayyum, & Bodla
(2010); and Sharma and Kumar (2011) but significantly differs from those conducted by Gakure,
Cheluget, Onyango and Keraro (2012); Mathuva (2010); and Filbeck, et al. (2005) which found a
significant relationship between average collection period and profitability. However, the overall model
is statistically significant, as it is indicated by the F-value of 9.989 (p<0.01). The model’s adjusted R2
implies that 31.2% of the variation in the profitability of the firms can be explained by the model. The
coefficients of the other variables included in the model are also highly significant. Return on Assets
increases with Firm Size (measured by the natural logarithm of Total Assets) and Sales Growth, and
decreases with financial debt. The Current Ratio which is a theoretical measure of liquidity has no
significant impact on profitability in case of manufacturing and construction firms in Kenya.
Model 2 tests the hypothesis that there is a significant relationship between Inventory
Conversion Period and profitability ROA. In this model, there are variables are the similar to those in
Model 1 except ACP which has been replaced with ICP. The regression result shows a significant
positive relation between ROA and ICP (p-value = 0.000). Thus, Ho2 hypothesis is rejected and is
concluded that ICP is statistically significant (p<0.01). This means that there exists a positive
relationship between the ICP and profitability. This finding is consistent with studies carried out on
conservative working capital policies (Mathuva, 2010).
©American Research Institute for Policy Development
www.aripd.org/ijat
12
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
This means that maintaining high inventory levels reduces the cost of possible interruptions in
the production process and the loss of business due to scarcity of products. Maintaining high levels of
inventories also helps in reducing the cost of supplying the products and protects the firm against price
fluctuations as a result of adverse macroeconomic factors as observed by Blinder and Maccirri (1991).
However, the results of this study are inconsistent with the results of the studies conducted by Padachi
(2006), Garcia-Teruel and Martinez-Solano (2007), Deloof (2003), Raheman and Nasr (2007) and
Raheman, Afza, Qayyum, & Bodla (2010) in their respective analysis of the relationship between
profitability and number of days of inventory. The other variables in model 2 are also significant. The
model's adjusted R2 is 44.4% with an F-value of 16.780 which is highly significant (p<0.01).
Model 3 tests the hypothesis that there is a significant relationship between Average Payment
Period and Profitability. The coefficient of APP shows a very significant positive relation between ROA
and APP. This positive relation confirms the positive correlation between ROA and APP in Table 4.2.
Ho3 hypothesis is rejected and is concluded that APP is statistically significant (p<0.01). This suggests
that, an increase in the number of day’s accounts payable by 1 day is associated with an increase in
profitability. Contrary to Deloof (2003), Raheman and Nasr (2007), Sharma and Kumar (2011) and
Padachi (2006), this finding holds that more profitable firms wait longer to pay their bills. This implies
that they withhold their payment to suppliers so as to take advantage of the cash available for their
working capital needs. The other variables in the model except current ratio are significant. The model's
adjusted R2 is 54.0% with an F-value of 24.273 which is highly significant (p<0.05).
Model 4 tests the hypothesis that there is a significant relationship between Cash Conversion
Cycle and profitability. The regression coefficient indicates a significant negative relation between CCC
and ROA Ho3 hypothesis is rejected and is concluded that CCC is statistically significant (p<0.1). This
supports the notion that the cash conversion cycle is negatively related with profitability. Shin and
Soenen (1998) argued that the negative relation between profits and the cash conversion cycle could be
explained by the market power or the market share, i.e., a shorter CCC because of bargaining power by
the suppliers and/or the customers as well as higher profitability due to market dominance. The other
variables in the model are also statistically significant except current ratio. The model’s adjusted R2 is
33.3% with an F-value of 10.874 which is highly significant (p<0.01).
Model 5 acts as a control model for the variables under study. The model was run so as to
provide an indicator as to the most significant variables affecting the study. The model shows that all the
variables included are highly significant at 1% level with an exception of firm size (significant at 10%)
and ACP, ICP and CR which are not significant. In this model, the ACP and the leverage are negatively
related with the firm's profitability while all the other variables exhibit a positive relationship. The
model's adjusted R2 is 54.7%% with an F-value of 18.045 which is highly significant (p<0.01).
7. Conclusion
Most of the Kenyan manufacturing firms have large amounts of cash invested in working
capital. It can therefore be expected that the way in which working capital is managed will have a
significant impact on profitability of those firms. The study found out existence of negative correlation
between Return on Assets and the firms average collection period and cash conversion cycle. However,
the study findings suggests that there is a positive correlation between Return on Inventory Holding
Period, Accounts Payment Period and. These results suggest that managers can create value for their
shareholders by reducing the number of day’s accounts receivable and increasing the accounts payment
period and inventories to a reasonable maximum.
8. Policy Implications
The results shows that for overall manufacturing and construction sectors, Working Capital
Management has a significant impact on profitability of the firms and plays a key role in value creation
for shareholders as longer Cash Conversion Cycle have negative impact on Profitability of a firm.
©American Research Institute for Policy Development
www.aripd.org/ijat
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
13
The negative association of Average Collection Period with Return on Assets, a measure of
profitability, helps the management in setting credit policy for the sector in general for the firms in
manufacturing and construction sector in Kenya. The study recommends a longer credit period for the
firms to realize higher profitability. There exists positive association between Inventory Turnover in
Days and Return on Assets for the manufacturing and construction sectors in Kenya as a whole, which
implies that firms, which maintain sufficiently high inventory levels, reduce costs of possible
interruptions in the production process and loss of business due to scarcity of products. Similarly there
is a positive relationship between Accounts payment period and Return on Assets of manufacturing and
construction firms in Kenya. The study recommends that the longer the accounts payable, the better the
profitability this could be due to good name created by suppliers and suppliers will not interrupt supplies
to the firm which in turn leads to smooth operation during the year and ends up with better profitability.
References
Akoto, R.K., Awunyo-Vitor, D., & Angmor, P.L. (2013). Working capital management and
profitability: Evidence from Ghanaian listed manufacturing firms. Journal of Economics and
International Finance, 5(9), 373-379.
Almazari, A.A. (2013).The Relationship between Working Capital Management and Profitability:
Evidence from Saudi Cement Companies. British Journal of Economics, Management & Trade,
4(1).
Barako, D.G., Hancock, P. & Izan, H.Y. (2006). Relationship between corporate governance attributes
and voluntary disclosures m annual reports: The Kenyan experience. Fin. Rep., Reg. Gov., 5: 126.
Blinder, A.S. & Maccini, L.J. (1991). The resurgence of inventory research: What have we learned?
Journal of Economic Survey, 5, 291-328.
Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of
Business Finance & Accounting, 30 (3/4), 573-587.
Eljelly, A. (2004). Liquidity-profitability tradeoff: An empirical investigation in an emerging market.
International Journal of Commerce and Management, 14 (2), 48-61.
Filbeck, G. & Thomas M.K. (2005). An analysis of working capital management results across
industries. Mid-American Journal of Business, 20 (2), 11-18.
Gakure, R., Cheluget, K.J. Onyango, J.A, & Keraro, V. (2012). Working capital management and
profitability of manufacturing firms listed at the Nairobi stock exchange. Prime Journal of
Business Administration and Management (BAM), 2(9), 680-686.
García-Teruel, P.J., & Martínez-Solano, P. (2007). Effects of working capital management on SME
profitability. International Journal of Managerial Finance, 3 (2), 164-177.
Gill, A., Biger, N., & Mathur, N. (2010). The relationship between working capital management and
profitability: Evidence from the United States. Business and Economics Journal, 4 (2), 1-9.
Gujarati, D.N., & Sangeetha (2008). Basic Econometrics (4th Ed.). New Delhi, India: Tata McGraw-Hill.
Gul, S., Khan, M. B., Raheman, S.U., Khan, M.T., Khan, M., & Khan, W. (2013). Working capital
management and performance of SME sector. European Journal of Business and management,
5(1), 60-68.
Horne, J.C., & Wachowicz J.M. (2000). Fundamentals of Financial Management. New York, NY:
Prentice Hall Publishers.
Huang, P.Y., Zhang, D.R., D. and Moffit, J S. (2009). Do artificial income smoothing and real income
smoothing contribute to firm value equivalently. Journal of Banking and Finance, 33: 224-233.
Jeng-Ren, C., Li, C., & Han-Wen, W. (2006). The determinants of working capital management.
Journal of American Academy of Business, Cambridge, 10 (1), 149-155.
Jose, M.L., Lancaster, C., & Stevens, J.L. (1996). Corporate return and cash conversion cycle. Journal
of Economics and Finance, 20(1), 33–46.
©American Research Institute for Policy Development
www.aripd.org/ijat
14
International Journal of Accounting and Taxation, Vol. 1 No. 1, December 2013
Kargar, J., & Blumenthal, R. A. (1994). Leverage impact of working capital in small businesses. TMA
Journal. 14(6), 46-53.
Makridakis, S., & Wheelwright, S. C. (1978). Interactive forecasting univariate and multivariate
methods. California: Holden-Day Inc.
Maradi, M., Salehi, M., & Arianpoor, A. (2012). A comparison of working capital management of
chemical and medicine listed companies in Tehran Stock Exchange. International Journal of
Business and Behavioral Science, 2 (5), 62-78.
Mathuva, D.M. (2010). Influence of working capital management components on corporate
profitability: A survey on Kenyan listed firms. Research Journal of Business Management 3 (1),
1-11.
Mukhopadhyay, D. (2004). Working Capital Management in Heavy Engineering Firms—A Case Study.
Accessed from myicwai.com/knowledgebank/fm48.
Nazir, M.S., & Afza, T. (2009). Impact of aggressive working capital management policy on firms’
profitability. The IUP Journal of Applied Finance, 15 (8), 19-30.
Nyabwanga, R.N., Ojera, P., Lumumba, M., Odondo, A.J., & Otieno, S. (2012). Effect of working
capital management practices on financial performance: A study of small scale enterprises in
Kisii South District, Kenya. African Journal of Business Management, 6 (18) 5807-5817.
Oladipupo, A.O., & Okafor, C.A. (2013). Relative contribution of working capital management to
corporate profitability and dividend payout ratio: Evidence from Nigeria. International Journal
of Business and Finance Research, 3(2), 11-20.
Omesa, N. W., Maniagi, G. M., Musiega, D., & Makori, G.A. (2013). Working capital management
and corporate performance: Special reference to manufacturing firms on Nairobi Securities
Exchange. International Journal of Innovative Research and Development, 2(9), 177-183.
Padachi, K. (2006). Trends in Working Capital Management and its Impact on Firms’ Performance: An
Analysis of Mauritian Small Manufacturing Firms. International Review of Business Research
Papers. 2 (2), 45 - 58.
Raheman, A., Afza, T., Qayyum, A., & Bodla, M.A. (2010). Working Capital Management and
Corporate Performance of Manufacturing Sector in Pakistan. International Research Journal of
Finance and Economics, Issue 47, 151-163.
Raheman, A., & Nasr, M. (2007). Working capital management and profitability case of Pakistan firms.
International Review of Business Research Papers, 3 (1), 279-300.
Samiloglu, F., & Demirgunes, K. (2008). The effect of working capital management on firm
profitability: Evidence from Turkey. The International Journal of Applied Economics and
Finance, 2(1), 44–50.
Sharma, A.K., & Kumar, S. (2011). Effect of working capital management on firm profitability:
Empirical evidence from India. Global Business Review, 12 (1) 159-173.
Shin, H.H., & Soenen, L. (1998). Efficiency of working capital management and corporate profitability.
Financial Practice and Education, 8(2), 37–45.
Smith, K., 1980. Profitability versus liquidity tradeoffs in working capital management. In: readings on
the management of working capital, Smith, K.V. (Ed). St. Paul, MM, West Publishing Firm,
USA, pp: 549-562.
Zariyawati, M. A., Annuar, M. N., Taufiq, H. & Rahim, A. S. A. (2008). Working capital management
and corporate performance: Case of Malaysia. Journal of Modern Accounting and Auditing, 5
(11), 47-54.
©American Research Institute for Policy Development
www.aripd.org/ijat